An applied Swiss-inspired curriculum combining algorithmic rigour, systems architecture, digital trust and practical engineering capability for modern technology leaders.
The BSc in Digital Health Technology at Brookfield School of Computing is engineered to provide deep competency across core computer science, systems design, and targeted domain applications. Students develop fluency in software craftsmanship, distributed architectures, algorithm optimization, and data governance.
Instruction balances rigorous theoretical foundations with practical code repositories, laboratory simulations, and ethical technology review aligned with modern international computing standards.
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| HLT101 | Foundations of Molecular Biology & Computational Genetics | Theory | Deconstruct DNA/RNA transcription, translation, genetic code degeneracy, chromosomal organization and mutations in Digital Health Technology. |
| HLT102 | Python for Biological Data & Biopython Lab | Practical | Parse FASTA and GenBank genomic records, calculate GC content and translate amino acid sequences using Biopython. |
| HLT103 | Discrete Mathematics, Combinatorics & Graph Theory in Biology | Theory | Model De Bruijn graphs for genome assembly, Eulerian paths, probability trees and genetic population matrices. |
| HLT104 | Linux Command Line & High-Performance Computing for Genomics Lab | Practical | Execute batch job scripts using Slurm, manipulate multi-gigabyte BAM files and automate bioinformatics pipelines. |
| HLT105 | Biological Databases & Information Systems (NCBI, Ensembl, UniProt) | Theory | Analyze biological database schemas, accession identifiers, ontology hierarchies (Gene Ontology) and curated data. |
| HLT106 | Database Querying, Entrez APIs & Data Mining Lab | Practical | Query NCBI databases programmatically using E-utilities and automate gene annotation downloads with Python. |
| HLT107 | Bioethics, Genetic Privacy & Human Subject Data Rights | Theory | Analyze genetic discrimination, GDPR/Swiss genetic privacy laws, informed consent and forensic DNA ethics. |
| HLT108 | Exploratory Visualization of Genomic & Clinical Data Lab | Practical | Plot chromosome ideograms, Manhattan plots, volcano plots and clinical survival curves using Python and R. |
| HLT109 | Technical Communication & Scientific Literature Synthesis in Digital Health Technology | Theory | Synthesize molecular biology literature, write reproducible experimental protocols and author clinical briefs. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| HLT201 | Sequence Alignment Algorithms: Dynamic Programming & Heuristics | Theory | Derive Needleman-Wunsch global alignment, Smith-Waterman local alignment, PAM/BLOSUM scoring matrices and BLAST. |
| HLT202 | BLAST, Multiple Sequence Alignment (Clustal) & Phylogeny Lab | Practical | Execute local BLAST searches, construct multiple sequence alignments and build phylogenetic trees in Python/MEGA. |
| HLT203 | Biostatistics & Statistical Genetics Foundations | Theory | Calculate Hardy-Weinberg equilibrium, linkage disequilibrium, chi-square association tests and odds ratios. |
| HLT204 | Biostatistical Analysis & Hypothesis Testing in R Lab | Practical | Execute differential gene expression tests, ANOVA and multiple testing corrections (FDR / Bonferroni) in R. |
| HLT205 | Next-Generation Sequencing (NGS) Technologies & Data Formats | Theory | Analyze Illumina, PacBio and Oxford Nanopore sequencing chemistry, base-calling, FASTQ formats and Phred scores. |
| HLT206 | NGS Quality Control & Read Trimming Lab (FastQC / Trimmomatic) | Practical | Assess sequencing quality with FastQC, trim low-quality adapters with Trimmomatic and inspect alignment stats. |
| HLT207 | Healthcare Data Standards: HL7, FHIR & SNOMED CT | Theory | Analyze Fast Healthcare Interoperability Resources (FHIR) JSON resources, LOINC lab codes and clinical ontologies. |
| HLT208 | Clinical FHIR API Development & Healthcare Integration Lab | Practical | Build a FHIR client application querying patient records, observations and diagnostic reports via REST APIs. |
| HLT209 | Applied Digital Health Technology First-Year Practicum: Genome Variant Analysis | Practical | Deliver an end-to-end genomic variant discovery study from raw sequencing reads to clinical annotation. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| HLT301 | Genome Assembly Algorithms, De Bruijn Graphs & Scaffolding | Theory | Deconstruct overlap-layout-consensus (OLC) and k-mer De Bruijn graph assemblers (SPAdes, Velvet) for contig building. |
| HLT302 | De Novo Genome Assembly & Annotation Lab | Practical | Assemble bacterial genomes from Illumina/Nanopore reads and annotate open reading frames using Prokka. |
| HLT303 | Read Mapping, Variant Calling & VCF Pipeline Architecture | Theory | Analyze Burrows-Wheeler Transform (BWA-MEM), SAM/BAM coordinate sorting and GATK best practices for variant calling. |
| HLT304 | GATK Variant Calling & SnpEff Clinical Annotation Lab | Practical | Execute BWA alignment, mark PCR duplicates, call SNPs/indels with GATK HaplotypeCaller and annotate with SnpEff. |
| HLT305 | Electronic Health Records (EHR) Systems & Clinical Data Warehousing | Theory | Design enterprise hospital information systems (HIS), clinical data repositories (CDR) and OMOP common data models. |
| HLT306 | OMOP Common Data Model & Clinical SQL Transformation Lab | Practical | Map disparate hospital clinical records into the standardized OMOP Common Data Model using SQL and Python. |
| HLT307 | Medical Image Computing: DICOM Standards & PACS Infrastructure | Theory | Analyze DICOM metadata structures, PACS image storage, CT/MRI Hounsfield units and radiology viewer architecture. |
| HLT308 | DICOM Image Processing & Volumetric Rendering Lab (SimpleITK) | Practical | Load, filter, segment and reconstruct 3D anatomical volumes from DICOM CT/MRI slices using SimpleITK. |
| HLT309 | Clinical Research Methods, Survival Analysis & Cox Regressions | Theory | Formulate Kaplan-Meier survival curves, log-rank tests and Cox proportional hazards regression models. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| HLT401 | Machine Learning in Clinical Diagnostics & Predictive Medicine | Theory | Model disease risk, sepsis onset, patient readmission and biomarker discovery using regularized regression and trees. |
| HLT402 | Clinical Predictive Modeling & ROC-AUC Validation Lab | Practical | Train and validate predictive risk models on MIMIC-IV clinical intensive care datasets with calibrated ROC-AUC scores. |
| HLT403 | RNA-Seq Transcriptomics & Differential Expression Analysis | Theory | Analyze RNA-seq library preparation, read count normalization (TPM, RPKM), negative binomial models and DESeq2. |
| HLT404 | DESeq2 Differential Expression & Pathway Enrichment Lab | Practical | Identify significantly upregulated/downregulated genes in R with DESeq2 and perform Gene Ontology pathway enrichment. |
| HLT405 | Deep Learning in Medical Imaging: CNNs for Radiology & Pathology | Theory | Deconstruct 2D/3D U-Net architectures, convolutional classifiers, attention gates and image segmentation in medicine. |
| HLT406 | U-Net Medical Image Tumor Segmentation Lab (PyTorch / MONAI) | Practical | Train a 3D U-Net model on MONAI / PyTorch to automatically segment brain tumors and lung nodules from MRI scans. |
| HLT407 | Health Data Security, HIPAA & Swiss Federal Patient Privacy Laws | Theory | Implement medical confidentiality standards, Swiss Electronic Patient Dossier (EPD) regulations and HIPAA security. |
| HLT408 | Clinical Pseudonymization & De-Identification Engine Lab | Practical | Build automated text pipelines to identify and redact Protected Health Information (PHI) from clinical narratives. |
| HLT409 | Industrial Digital Health Technology Team Project: Digital Health Solution Studio | Practical | Engineer a production-ready clinical decision support service integrating FHIR data, AI models and clinician UI. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| HLT501 | Structural Bioinformatics, Protein Folding & AlphaFold Modeling | Theory | Analyze secondary/tertiary protein structure, Ramachandran plots, contact maps and AlphaFold neural architectures. |
| HLT502 | AlphaFold & Molecular Docking Simulation Lab (AutoDock) | Practical | Predict 3D protein structures using AlphaFold/ColabFold and simulate small molecule ligand docking with AutoDock Vina. |
| HLT503 | Single-Cell RNA-Seq (scRNA-Seq) & Cell Type Clustering | Theory | Analyze droplet-based microfluidics (10x Genomics), UMI counting, cell barcode filtering and Seurat/Scanpy workflows. |
| HLT504 | Scanpy Single-Cell Transcriptomic Analysis Lab | Practical | Process scRNA-seq datasets with Scanpy, compute PCA/UMAP embeddings, cluster cell types and identify marker genes. |
| HLT505 | Clinical Decision Support Systems (CDSS) & Rule-Based Engines | Theory | Architect Arden Syntax medical logic modules, clinical guidelines integration and drug-drug interaction alerts. |
| HLT506 | CDSS Rules Engine & Alert Workflow Integration Lab | Practical | Implement an automated clinical drug interaction checking service with clinician alert suppression safeguards. |
| HLT507 | Swiss & Global Medical Device Software Regulations (MDR / SaMD) | Theory | Audit Software as a Medical Device (SaMD) under EU MDR 2017/745, ISO 13485 quality systems and IEC 62304 lifecycles. |
| HLT508 | Clinical AI Validation, Bias Auditing & Calibration Lab | Practical | Audit clinical neural network predictions for racial/gender demographic disparities and perform Brier score calibration. |
| HLT509 | Senior Digital Health Technology Capstone Project: Architecture & Clinical Protocol | Practical | Author comprehensive clinical protocols, computational pipeline specifications and data governance approvals. |
| Code | Module Title | Type | Discipline & Learning Outcome |
|---|---|---|---|
| HLT601 | Emerging Frontiers: Precision Medicine, Multi-Omics & Digital Twins | Theory | Evaluate genomic personalized oncology, spatial transcriptomics, metagenomics and patient physiological digital twins. |
| HLT602 | Senior Digital Health Technology Capstone Project: Production System Implementation | Practical | Engineer the complete computational biology pipeline and clinical web platform with reproducible workflows (Nextflow). |
| HLT603 | Senior Digital Health Technology Capstone Project: Clinical Benchmarking & Validation | Practical | Validate computational sensitivity and specificity against gold-standard clinical cohorts and peer-reviewed datasets. |
| HLT604 | Executive Health Technology Leadership & Healthcare Operations | Theory | Present computational precision medicine roadmaps and digital health ROI to hospital boards and healthcare leaders. |
| HLT605 | Production Deployment, Nextflow Workflows & Dockerization Lab | Practical | Package reproducible multi-stage Nextflow pipelines with Docker containers on cloud computing clusters. |
| HLT606 | Societal Implications: Genetic Engineering, Eugenics & Health Equity | Theory | Analyze CRISPR gene editing ethics, synthetic biology hazards, health disparity access barriers and human dignity. |
| HLT607 | Industry Technical Health Portfolio & Clinical Protocol Defense | Practical | Defend algorithmic validity, biological interpretation and patient privacy safeguards before an expert medical review board. |
| HLT608 | Peer Review, Scientific Dissemination & Open Biomedical Data | Theory | Author peer-reviewable scientific manuscripts according to STROBE/TRIPOD guidelines and open-source data standards. |
| HLT609 | Final Digital Health Technology Capstone Project Demonstration & Oral Defense | Practical | Conduct a live demonstration of the computational health platform and pass an oral academic dissertation examination in Digital Health Technology. |
Secondary School Diploma / Swiss Matura / International Baccalaureate or recognized foreign upper-secondary certificate. English proficiency IELTS 6.0+ or equivalent.
Brookfield School of Computing is an independent private education institution in formation. Academic programmes, entry requirements, fees and awards are subject to institutional review and applicable Swiss legal regulations.